code: def model_config(
      model, instance_type=None, role=None, image_uri=None
  ):
      """Export Airflow model config from a SageMaker model
  
      Args:
          model (sagemaker.model.Model): The Model object from which to export the Airflow config
          instance_type (str): The EC2 instance type to deploy this Model to. For
              example, 'ml.p2.xlarge'
          role (str): The ``ExecutionRoleArn`` IAM Role ARN for the model
          image_uri (str): An Docker image URI to use for deploying the model
  
      Returns:
          dict: Model config that can be directly used by SageMakerModelOperator
              in Airflow. It can also be part of the config used by
              SageMakerEndpointOperator and SageMakerTransformOperator in Airflow.
      """
      s3_operations = {}
      model.image_uri = image_uri or model.image_uri
  
      if isinstance(model, sagemaker.model.FrameworkModel):
          container_def = prepare_framework_container_def(
              model, instance_type, s3_operations
          )
      else:
          container_def = model.prepare_container_def()
          base_name = utils.base_name_from_image(container_def["Image"])
          model.name = model.name or utils.name_from_base(base_name)
  
      primary_container = session._expand_container_def(container_def)
  
      config = {
          "ModelName": model.name,
          "PrimaryContainer": primary_container,
          "ExecutionRoleArn": role or model.role,
      }
  
      if model.vpc_config:
          config["VpcConfig"] = model.vpc_config
  
      if s3_operations:
          config["S3Operations"] = s3_operations
  
      return config
  
imports: from __future__ import print_function, absolute_import
  import os
  import re
  import sagemaker
  from sagemaker import fw_utils, job, utils, s3, session, vpc_utils
  from sagemaker.amazon import amazon_estimator
  from sagemaker.tensorflow import TensorFlow
  from sagemaker.estimator import EstimatorBase
  from sagemaker.processing import Processor
  from sagemaker.utils import format_tags
label_desc: Use image node_id 13 for calling a global function with example usage: model_config(model, instance_type, role, image_uri) and returns: config